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RESLVE: Leveraging User Interest to Improve Entity Disambiguation on Short Text

Abstract

We address the Named Entity Disambiguation (NED) problem for short, user-generated texts on the social Web. In such settings, the lack of linguistic features and sparse lexical context result in a high degree of ambiguity and sharp performance drops of nearly 50% in the accuracy of conventional NED systems. We handle these challenges by developing a general model of user-interest with respect to a personal knowledge context and instantiate it using Wikipedia. We conduct systematic evaluations using individuals' posts from Twitter, YouTube, and Flickr and demonstrate that our novel technique is able to achieve performance gains beyond state-of-the-art NED methods.

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Authors
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Citation
Category
Paper in Conference Proceedings or in Workshop Proceedings (Poster)
Event Title
International World Wide Conference
Divisions
Multimedia Information Systems
Subjects
Webmanagement
Event Location
Rio de Janeiro
Event Type
Conference
Series Name
WWW 2013
Date
05 May 2013
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